[Topic-models] Comparison of different tools for LDA

Kowalski, Radoslaw radoslaw.kowalski.14 at ucl.ac.uk
Thu Jun 9 05:08:21 EDT 2016

Hi Shayan,

I would discourage you from using R because it has few robust packages for deep learning. My opinion is that deep learning is likely going to be used a lot in topic modelling in the future. In where I am in UCL we often use gensim but the list of relevant python packages is much longer. Gensim is not always a golden solution to every topic model problem. You may find easier to use python packages for specific problems.

All the best,

Radoslaw Kowalski

PhD Student


Consumer Data Research Centre

UCL Department of Political Science


T:  020 3108 1098 x51098

E:  radoslaw.kowalski.14 at ucl.ac.uk<mailto:n.vij at ucl.ac.uk>

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From: topic-models-bounces at lists.cs.princeton.edu <topic-models-bounces at lists.cs.princeton.edu> on behalf of Shayan A Tabrizi <shayantabrizi at gmail.com>
Sent: 08 June 2016 21:57:25
To: topic-models
Subject: [Topic-models] Comparison of different tools for LDA

Dear Topic-Modelers,

There are several tools for LDA. But I don't know which one is better and when? I wonder if anyone could guide me in choosing one toolbox. My priorities are ease-of-use and supporting various variations and extensions of LDA.
Some but not all of the candidates are:
1- MALLET (Java)
2- gensim (Python)
3- topicmodels (R)
4- Stanford Topic Modeling Toolbox

Thanks in advance,
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